The Influence of Learning Styles on Learners in E-Learning Environments: An Empirical Study

The purpose of this study was to compare the effects of e-learning versus those of traditional instructor-based learning, on student learning, based on student learning styles. Another goal was to determine if e-learning is more effective for those with a particular learning style. The Kolb Learning Style Inventory (LSI) measured the learning styles of students. This post-test, intact-group design examined the dependent variable of student knowledge based on the learning style of each subject and the learning method to which each was exposed. The results revealed that for the instructor-based learning class (traditional), the learning style was irrelevant, but for the web-based learning class (e-learning), the learning style was significantly important. The results indicated that students with the Assimilator learning style (these learn best through lecture, papers and analogies) and the Converger learning style (these learn best through laboratories, field work and observations) achieved a better result with the e-learning (web-based) method.

An E-Learning Investigation into Learning Style Adaptivity

Abstrac

Learning styles, personalisation and adaptable e-learning

Common Learning Management Systems (for example Moodle [1] and Blackboard [2]) are limited in the amount of personalisation that they can offer the learner. They are used widely and do offer a number of tools for instructors to enable them to create and manage courses, however, they do not allow for the learner to have a unique personalised learning experience. The e-Learning platform iLearn offers personalisation for the learner in a number of ways and one way is to offer the specific learning material to the learner based on the learner's learning style. Learning styles and how we learn is a vast research area. Brusilovsky and Millan [3] state that learning styles are typically defined as the way people prefer to learn. Examples of commonly used learning styles are Kolb Learning Styles Theory [4], Felder and Silverman Index of Learning Styles [5], VARK [6] and Honey and Mumford Index of Learning Styles [7] and many research projects (SMILE [8], INSPIRE [9], iWeaver [10] amonst others) attempt to incorporate these learning styles into adaptive e-Learning systems. This paper describes how learning styles are currently being used within the area of adaptive e-Learning. The paper then gives an overview of the iLearn project and also how iLearn is using the VARK learning style to enhance the platform's personalisation and adaptability for the learner. This research also describes the system's design and how the learning style is incorporated into the system design and semantic framework within the learner's profile

The Relationship Between Preferred Modal Learning Style and Patterns of Use and Completion of an Online Project Management Training Programme

This paper reports the results of a pilot study, conducted to observe and evaluate the patterns of use and completion of a set of project management units and to identify any relationships between these factors and learning style. The aim of the study was to gather data on which to base a subsequent software development project, based around personalising the learning materials. The participants were adult professionals employed in public sector organisations in the UK and the study was based within a real business e-learning environment. Data regarding preferred learning style was collected via a questionnaire and usage, progress and completion rates were gathered from computer logging data, with user permission. To assess preferred learning style, the VARK inventory (Fleming and Mills, 1992) was used; this categorises learners according to modal preference for learning: Visual, Auditory, Read/write and Kinaesthetic. The results showed that learners with a preferred Visual mode showed the best record for completions and were characterised by frequent usage, but for relatively shorter study durations. In contrast, learners preferring the Auditory modality had the lowest proportion of completions, and also this group logged on less frequently but for longer study periods. Learners with a preferred Kinaesthetic mode were characterised by the highest proportion of ‘In-Process’ learners (who were regularly using the system but not yet completed). The paper concludes with a proposal to build a personalisable learning environment incorporating specific modal features. A further study will then observe more closely the interaction between preferred modal learning style, mode of presentation and usage and performance. Keywords: VARK, modal learning style, business e-learning, project managemen

Using styles for more effective learning in multicultural and e-learning environments

Purpose – This Special Issue contains selected papers from the thirteenth annual European Learning Styles Information Network (ELSIN) conference held in Ghent, Belgium in June 2008. One of the key aims of ELSIN is to promote understanding of individual learning and cognitive differences through the dissemination of international multidisciplinary research about learning and cognitive styles and strategies of learning and thinking. Design/methodology/approach – Three papers within this special issue consider how style differences can inform the development of e-learning opportunities to enhance the learning of all (Vigentini; Kyprianidou, Demetriadis, Pombortsis and Karatasios; Zhu, Valcke and Schellens). The influence of culture on learning is also raised in the paper of Zhu and colleagues and those of Sulimma and Eaves which both focus more directly on cultural influences on style, learning and teaching. Findings – A number of key themes permeate the studies included in this Special Edition such as: the nature of styles; the intrinsic difficulty of isolating style variables from other variables impacting on performance; inherent difficulties in choosing the most appropriate style measures; the potential of e-learning to attend to individual learning differences; the role of culture in informing attitudes and access to learning; the development of constructivist learning environments to support learning through an understanding of individual differences; and most importantly how one can apply such insights about individual differences to inform and enhance instruction. Originality/value – The papers in this Special Issue contribute to enhanced knowledge about the value of style differences to design constructive learning environments in multicultural and e-learning contexts

Empirical evaluation of an adaptive e-learning system and the effects of knowledge, learning styles and multimedia mode on student achievement

This paper presents an empirical evaluation of an adaptive e-learning system (AES). The system was evaluated in an experimental research. During the 9 weeks of experimentation, the students studied the learning material in two randomly allocated groups, an experimental group using the AES and a control group using the non-AES. Research findings are described as follows. Students who learned using the AES performed better significantly than those who learned using the non-AES. The implementation of test repetition as a function of knowledge adaptation in the AES increased student achievement significantly. When the effect of test repetition was removed, the implementation of learning style and multimedia mode adaptation in the AES was still found to have significant effect upon student performance. Students whose learning style and multimedia preferences were matched with the system achieved better results

The design and implementation of an adaptive e-learning system

This paper describes the design and implementation of an adaptive e-learning system that provides a template for different learning materials as well as a student model that incorporates five distinct student characteristics as an aid to learning: primary characteristics are prior knowledge, learning style and the presence or absence of animated multimedia aids (multimedia mode); secondary characteristics include page background preference and link colour preference. The use of multimedia artefacts as a student characteristic has not previously been implemented or evaluated. The system development consists of a requirements analysis, design and implementation. The design models including use case diagrams, conceptual design, sequence diagrams, navigation design and presentation design are expressed using Unified Modelling Language (UML). The adaptive e-learning system was developed in a template implemented using Java Servlets, XHTML, XML, JavaScript and HTML. The template is a domain-independent adaptive e-learning system that has functions of both adaptivity and adaptability

The Impact of Learning Style Adaptivity in Teaching Computer Security

Teaching computer security is one of the most challenging tasks in computer science, because of the need to successfully integrate abstract concepts and practical applications. Several e-learning systems have been developed to address this issue. However, they usually provide the same material in the same sequence irrespective of the characteristics of the students, such as their knowledge level and learning style. In this paper, an approach to learning style adaptivity is proposed for the teaching of computer security. An e-learning system was developed to provide more personalised and adaptive learning, based on the information perception style of the Felder-Silverman model. This is the dimension of learning style, which has received the least attention in published research. In the approach, a personalised sequence of learning material is generated based on an individual learning style. The approach is evaluated in order to determine its effectiveness in learning provision. An experiment conducted with sixty subjects produced significant results. They indicate that matching computer security learning material, according to the learning style of the students, yields significantly better learning gain and student satisfaction than without matchin